Infectious keratitis in pediatric population aged less than two years: a tertiary eye institute experience.

BACKGROUND: Infectious keratitis is a serious ocular condition, which can lead to corneal scarring, vision loss, and even blindness. Pediatric infectious keratitis accounts for about 13% of all cases, although there is a lack of comprehensive data regarding keratitis in less than two years of age population group. This study was aimed to determine predisposing factors, clinical characteristics, microbial profile, and management of infectious keratitis in a population of children aged less than two years. MATERIALS AND METHODS: A retrospective study was carried out in a tertiary eye institute over a period of 18 years from July 2005 to December 2022. Collected data was analyzed for demographics, predisposing factors, clinical features, and treatment methods. RESULTS: Fifty-seven cases of keratitis were identified. Age of the patients ranged from 1 to 24 months (Median: 6, interquartile range: 2-10). Thirty cases were male (52.6%). Predisposing factors were identified in 39 cases (68.4%): consisting of prior ocular trauma (n = 15), previous intraocular surgery (n = 11), ocular surface disease (n = 10), nasolacrimal duct obstruction (n = 4), prematurity (n = 3), developmental delay (n = 2), TORCH infection (n = 1), and contact lens (n = 1). Corneal thinning was observed in 29 eyes (50.9%), which progressed to perforation in 13 eyes (22.8%). Three patients developed endophthalmitis (95% CI, 1.5-13.4%). Most eyes had negative smear (60.4%) and culture (59.6%) results. Pseudomonas aeruginosa was the most common microorganism (11 of 21). Candida albicans was isolated in one case. In vitro susceptibility results showed good coverage of the combined ceftazidime and vancomycin regimen (100%). Surgical procedures were carried out in 35 eyes (61.4%) and 15 eyes required tectonic procedures (26.3%). CONCLUSION: Despite good coverage of medical treatment over cultured isolates, surgical tectonic intervention was required in nearly a quarter of cases to resolve the corneal infection. This finding indicates the necessity of prompt patient referring, corneal sampling and initiation of the treatment.

Applications of Artificial Intelligence in Diagnosis of Dry Eye Disease: A Systematic Review and Meta-Analysis.

PURPOSE: Clinical diagnosis of dry eye disease is based on a subjective Ocular Surface Disease Index questionnaire or various objective tests, however, these diagnostic methods have several limitations. METHODS: We conducted a comprehensive review of articles discussing various applications of artificial intelligence (AI) models in the diagnosis of the dry eye disease by searching PubMed, Web of Science, Scopus, and Google Scholar databases up to December 2022. We initially extracted 2838 articles, and after removing duplicates and applying inclusion and exclusion criteria based on title and abstract, we selected 47 eligible full-text articles. We ultimately selected 17 articles for the meta-analysis after applying inclusion and exclusion criteria on the full-text articles. We used the Standards for Reporting of Diagnostic Accuracy Studies to evaluate the quality of the methodologies used in the included studies. The performance criteria for measuring the effectiveness of AI models included area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy. We calculated the pooled estimate of accuracy using the random-effects model. RESULTS: The meta-analysis showed that pooled estimate of accuracy was 91.91% (95% confidence interval: 87.46-95.49) for all studies. The mean (±SD) of area under the receiver operating characteristic curve, sensitivity, and specificity were 94.1 (±5.14), 89.58 (±6.13), and 92.62 (±6.61), respectively. CONCLUSIONS: This study revealed that AI models are more accurate in diagnosing dry eye disease based on some imaging modalities and suggested that AI models are promising in augmenting dry eye clinics to assist physicians in diagnosis of this ocular surface condition.

Cell Type-Specific Extracellular Vesicles and Their Impact on Health and Disease.

Extracellular vesicles (EVs), a diverse group of cell-derived exocytosed particles, are pivotal in mediating intercellular communication due to their ability to selectively transfer biomolecules to specific cell types. EVs, composed of proteins, nucleic acids, and lipids, are taken up by cells to affect a variety of signaling cascades. Research in the field has primarily focused on stem cell-derived EVs, with a particular focus on mesenchymal stem cells, for their potential therapeutic benefits. Recently, tissue-specific EVs or cell type-specific extracellular vesicles (CTS-EVs), have garnered attention for their unique biogenesis and molecular composition because they enable highly targeted cell-specific communication. Various studies have outlined the roles that CTS-EVs play in the signaling for physiological function and the maintenance of homeostasis, including immune modulation, tissue regeneration, and organ development. These properties are also exploited for disease propagation, such as in cancer, neurological disorders, infectious diseases, autoimmune conditions, and more. The insights gained from analyzing CTS-EVs in different biological roles not only enhance our understanding of intercellular signaling and disease pathogenesis but also open new avenues for innovative diagnostic biomarkers and therapeutic targets for a wide spectrum of medical conditions. This review comprehensively outlines the current understanding of CTS-EV origins, function within normal physiology, and implications in diseased states.

Chlorine-Induced Toxicity on Murine Cornea: Exploring the Potential Therapeutic Role of Antioxidants.

Chlorine (Cl2) exposure poses a significant risk to ocular health, with the cornea being particularly susceptible to its corrosive effects. Antioxidants, known for their ability to neutralize reactive oxygen species (ROS) and alleviate oxidative stress, were explored as potential therapeutic agents to counteract chlorine-induced damage. In vitro experiments using human corneal epithelial cells showed decreased cell viability by chlorine-induced ROS production, which was reversed by antioxidant incubation. The mitochondrial membrane potential decreased due to both low and high doses of Cl2 exposure; however, it was recovered through antioxidants. The wound scratch assay showed that antioxidants mitigated impaired wound healing after Cl2 exposure. In vivo and ex vivo, after Cl2 exposure, increased corneal fluorescein staining indicates damaged corneal epithelial and stromal layers of mice cornea. Likewise, Cl2 exposure in human ex vivo corneas led to corneal injury characterized by epithelial fluorescein staining and epithelial erosion. However, antioxidants protected Cl2-induced damage. These results highlight the effects of Cl2 on corneal cells using in vitro, ex vivo, and in vivo models while also underscoring the potential of antioxidants, such as vitamin A, vitamin C, resveratrol, and melatonin, as protective agents against acute chlorine toxicity-induced corneal injury. Further investigation is needed to confirm the antioxidants' capacity to alleviate oxidative stress and enhance the corneal healing process.

Integrating a Fundus Camera with High-Frequency Ultrasound for Precise Ocular Lesion Assessment.

Ultrasound A-scan is an important tool for quantitative assessment of ocular lesions. However, its usability is limited by the difficulty of accurately localizing the ultrasound probe to a lesion of interest. In this study, a transparent LiNbO3 single crystal ultrasound transducer was fabricated, and integrated with a widefield fundus camera to guide the ultrasound local position. The electrical impedance, phase spectrum, pulse-echo performance, and optical transmission spectrum of the ultrasound transducer were validated. The novel fundus camera-guided ultrasound probe was tested for in vivo measurement of rat eyes. Anterior and posterior segments of the rat eye could be unambiguously differentiated with the fundus photography-guided ultrasound measurement. A model eye was also used to verify the imaging performance of the prototype device in the human eye. The prototype shows the potential of being used in the clinic to accurately measure the thickness and echogenicity of ocular lesions in vivo.

All about traumatic cataracts: narrative review.

Ocular trauma is an important cause of monocular blindness worldwide. Injury to the lens after blunt or penetrating trauma is common and can result in vision impairment. Selecting the most appropriate therapeutic approaches depends on factors such as patients' age, mechanism of trauma, and underlying clinical conditions. Early management, especially within childhood, is essential because of the difficulties involved in examination; anatomical variations; as well as accompanying intraocular inflammation, amblyopia, or vitreoretinal adhesions. The objective of this study was to provide a comprehensive review of the epidemiology and clinical management of traumatic cataract, highlighting the significance of accurate diagnosis and selection of the optimal therapeutic approach.

Performance of ChatGPT in Diagnosis of Corneal Eye Diseases.

PURPOSE: The aim of this study was to assess the capabilities of ChatGPT-4.0 and ChatGPT-3.5 for diagnosing corneal eye diseases based on case reports and compare with human experts. METHODS: We randomly selected 20 cases of corneal diseases including corneal infections, dystrophies, and degenerations from a publicly accessible online database from the University of Iowa. We then input the text of each case description into ChatGPT-4.0 and ChatGPT-3.5 and asked for a provisional diagnosis. We finally evaluated the responses based on the correct diagnoses, compared them with the diagnoses made by 3 corneal specialists (human experts), and evaluated interobserver agreements. RESULTS: The provisional diagnosis accuracy based on ChatGPT-4.0 was 85% (17 correct of 20 cases), whereas the accuracy of ChatGPT-3.5 was 60% (12 correct cases of 20). The accuracy of 3 corneal specialists compared with ChatGPT-4.0 and ChatGPT-3.5 was 100% (20 cases, P = 0.23, P = 0.0033), 90% (18 cases, P = 0.99, P = 0.6), and 90% (18 cases, P = 0.99, P = 0.6), respectively. The interobserver agreement between ChatGPT-4.0 and ChatGPT-3.5 was 65% (13 cases), whereas the interobserver agreement between ChatGPT-4.0 and 3 corneal specialists was 85% (17 cases), 80% (16 cases), and 75% (15 cases), respectively. However, the interobserver agreement between ChatGPT-3.5 and each of 3 corneal specialists was 60% (12 cases). CONCLUSIONS: The accuracy of ChatGPT-4.0 in diagnosing patients with various corneal conditions was markedly improved than ChatGPT-3.5 and promising for potential clinical integration. A balanced approach that combines artificial intelligence-generated insights with clinical expertise holds a key role for unveiling its full potential in eye care.

Hydrogel-Based Skin Regeneration.

The skin is subject to damage from the surrounding environment. The repair of skin wounds can be very challenging due to several factors such as severe injuries, concomitant infections, or comorbidities such as diabetes. Different drugs and wound dressings have been used to treat skin wounds. Tissue engineering, a novel therapeutic approach, revolutionized the treatment and regeneration of challenging tissue damage. This field includes the use of synthetic and natural biomaterials that support the growth of tissues or organs outside the body. Accordingly, the demand for polymer-based therapeutic strategies for skin tissue defects is significantly increasing. Among the various 3D scaffolds used in tissue engineering, hydrogel scaffolds have gained special significance due to their unique properties such as natural mimicry of the extracellular matrix (ECM), moisture retention, porosity, biocompatibility, biodegradability, and biocompatibility properties. First, this article delineates the process of wound healing and conventional methods of treating wounds. It then presents an examination of the structure and manufacturing methods of hydrogels, followed by an analysis of their crucial characteristics in healing skin wounds and the most recent advancements in using hydrogel dressings for this purpose. Finally, it discusses the potential future advancements in hydrogel materials within the realm of wound healing.

In praise of povidone-iodine application in ophthalmology.

Polyvinyl pyrrolidone or povidone-iodine (PVP-I) is a water-soluble complex formed by the combination of iodine and a water-soluble polymer, polyvinyl pyrrolidone. This complex exerts bactericidal, fungicidal, and virucidal action by gradually releasing free iodine at the site of application to react with pathogens. In ophthalmology, PVP-I is used as a disinfectant and antiseptic agent for preoperative preparation of the skin and mucous membranes and for treating contaminated wounds. PVP-I has been shown to reduce effectively the risk of endophthalmitis in various ocular procedures, including cataract surgery and intravitreal injections; however, it has also been used in the treatment of conjunctivitis, keratitis, and endophthalmitis, with promising results especially in low-resource situations. PVP-I has been associated with complications such as postoperative eye pain, persistent corneal epithelial defects, ocular inflammation, and an attendant risk of keratitis. In cases of poor PVP-I tolerance, applying PVP-I at lower concentrations or using alternative antiseptics such as chlorhexidine should be considered. We provide an update on the efficacy of PVP-I in the prophylaxis and treatment of conjunctivitis, keratitis, and endophthalmitis and a comprehensive analysis of the current literature regarding the use of PVP-I in the management of these ocular conditions. Also, PVP-I-related adverse effects and toxicities and its alternatives are discussed. The goal is to present a thorough evaluation of the available evidence and to offer practical recommendations for clinicians regarding the therapeutic usage of PVP-I in ophthalmology.

The Potential of Mesenchymal Stem/Stromal Cell Therapy in Mustard Keratopathy: Discovering New Roads to Combat Cellular Senescence.

Mesenchymal stem/stromal cells (MSCs) are considered a valuable option to treat ocular surface disorders such as mustard keratopathy (MK). MK often leads to vision impairment due to corneal opacification and neovascularization and cellular senescence seems to have a role in its pathophysiology. Herein, we utilized intrastromal MSC injections to treat MK. Thirty-two mice were divided into four groups based on the exposure to 20 mM or 40 mM concentrations of mustard and receiving the treatment or not. Mice were clinically and histopathologically examined. Histopathological evaluations were completed after the euthanasia of mice after four months and included hematoxylin and eosin (H&E), CK12, and beta-galactosidase (ß-gal) staining. The treatment group demonstrated reduced opacity compared to the control group. While corneal neovascularization did not display significant variations between the groups, the control group did register higher numerical values. Histopathologically, reduced CK12 staining was detected in the control group. Additionally, ß-gal staining areas were notably lower in the treatment group. Although the treated groups showed lower severity of fibrosis compared to the control groups, statistical difference was not significant. In conclusion, it seems that delivery of MSCs in MK has exhibited promising therapeutic results, notably in reducing corneal opacity. Furthermore, the significant reduction in the ß-galactosidase staining area may point towards the promising anti-senescence potential of MSCs.

From the diagnosis of infectious keratitis to discriminating fungal subtypes; a deep learning-based study.

Infectious keratitis (IK) is a major cause of corneal opacity. IK can be caused by a variety of microorganisms. Typically, fungal ulcers carry the worst prognosis. Fungal cases can be subdivided into filamentous and yeasts, which shows fundamental differences. Delays in diagnosis or initiation of treatment increase the risk of ocular complications. Currently, the diagnosis of IK is mainly based on slit-lamp examination and corneal scrapings. Notably, these diagnostic methods have their drawbacks, including experience-dependency, tissue damage, and time consumption. Artificial intelligence (AI) is designed to mimic and enhance human decision-making. An increasing number of studies have utilized AI in the diagnosis of IK. In this paper, we propose to use AI to diagnose IK (model 1), differentiate between bacterial keratitis and fungal keratitis (model 2), and discriminate the filamentous type from the yeast type of fungal cases (model 3). Overall, 9329 slit-lamp photographs gathered from 977 patients were enrolled in the study. The models exhibited remarkable accuracy, with model 1 achieving 99.3%, model 2 at 84%, and model 3 reaching 77.5%. In conclusion, our study offers valuable support in the early identification of potential fungal and bacterial keratitis cases and helps enable timely management.

Artificial Intelligence and Infectious Keratitis: Where Are We Now?

Infectious keratitis (IK), which is one of the most common and catastrophic ophthalmic emergencies, accounts for the leading cause of corneal blindness worldwide. Different pathogens, including bacteria, viruses, fungi, and parasites, can cause IK. The diagnosis and etiology detection of IK pose specific challenges, and delayed or incorrect diagnosis can significantly worsen the outcome. Currently, this process is mainly performed based on slit-lamp findings, corneal smear and culture, tissue biopsy, PCR, and confocal microscopy. However, these diagnostic methods have their drawbacks, including experience dependency, tissue damage, cost, and time consumption. Diagnosis and etiology detection of IK can be especially challenging in rural areas or in countries with limited resources. In recent years, artificial intelligence (AI) has opened new windows in medical fields such as ophthalmology. An increasing number of studies have utilized AI in the diagnosis of anterior segment diseases such as IK. Several studies have demonstrated that AI algorithms can diagnose and detect the etiology of IK accurately and fast, which can be valuable, especially in remote areas and in countries with limited resources. Herein, we provided a comprehensive update on the utility of AI in IK.